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ICMLA
2003
10 years 1 months ago
The Consolidation of Neural Network Task Knowledge
— Fundamental to the problem of lifelong machine learning is how to consolidate the knowledge of a learned task within a long-term memory structure (domain knowledge) without the...
Daniel L. Silver, Peter McCracken
ICMLA
2003
10 years 1 months ago
Fast Class-Attribute Interdependence Maximization (CAIM) Discretization Algorithm
– Discretization is a process of converting a continuous attribute into an attribute that contains small number of distinct values. One of the major reasons for discretizing an a...
Lukasz A. Kurgan, Krzysztof J. Cios
ICMLA
2003
10 years 1 months ago
Robust Support Vector Machines for Anomaly Detection in Computer Security
— Using the 1998 DARPA BSM data set collected at MIT’s Lincoln Labs to study intrusion detection systems, the performance of robust support vector machines (RVSMs) was compared...
Wenjie Hu, Yihua Liao, V. Rao Vemuri
ICMLA
2003
10 years 1 months ago
Reinforcement Learning Task Clustering
This work represents the first step towards a task library system in the reinforcement learning domain. Task libraries could be useful in speeding up the learning of new tasks th...
James L. Carroll, Todd S. Peterson, Kevin D. Seppi
ICMLA
2003
10 years 1 months ago
A Distributed Reinforcement Learning Approach to Pattern Inference in Go
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...
Myriam Abramson, Harry Wechsler
ICMLA
2004
10 years 1 months ago
Planning with predictive state representations
Predictive state representation (PSR) models for controlled dynamical systems have recently been proposed as an alternative to traditional models such as partially observable Mark...
Michael R. James, Satinder P. Singh, Michael L. Li...
ICMLA
2004
10 years 1 months ago
Variable resolution discretization in the joint space
We present JoSTLe, an algorithm that performs value iteration on control problems with continuous actions, allowing this useful reinforcement learning technique to be applied to p...
Christopher K. Monson, David Wingate, Kevin D. Sep...
ICMLA
2004
10 years 1 months ago
A new discrete binary particle swarm optimization based on learning automata
: The particle swarm is one of the most powerful methods for solving global optimization problems. This method is an adaptive algorithm based on social-psychological metaphor. A po...
Reza Rastegar, Mohammad Reza Meybodi, Kambiz Badie
ICMLA
2004
10 years 1 months ago
LASSO: a learning architecture for semantic web ontologies
Expressing web page content in a way that computers can understand is the key to a semantic web. Generating ontological information from the web automatically using machine learni...
Christopher N. Hammack, Stephen D. Scott
ICMLA
2004
10 years 1 months ago
Two new regularized AdaBoost algorithms
AdaBoost rarely suffers from overfitting problems in low noise data cases. However, recent studies with highly noisy patterns clearly showed that overfitting can occur. A natural s...
Yijun Sun, Jian Li, William W. Hager
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